Accessing a group of objects can be a cumbersome process, as it requires coordination among the objects. Conventionally the objects in a group are identified manually and are accessed manually. There exist some techniques to group a set of objects automatically. However to access the group, the user has to access the group manually. It is time consuming and the efficiency of the process is subject to the skills of the user. In an example, for displaying a set of objects in an image, the user may need to identify various objects and then select an option to display or highlight the group.
Analysis of images and documents are very important in diagnosis and data management systems. To analyze an image or document, it can be essential to visually highlight, bookmark and annotate similar or correlated objects in the image or document. At present, the workflow for the same is manual and time consuming. For example, in the case of analyzing a medical image, it is often essential to identify various objects such as fat deposits or calcium deposits in the image accurately. Many times the physician or radiologist will need to identify each object separately. This identification is subject to errors as the physician may miss identifying one or more similar objects in the image.
There exist some techniques to identify similar objects in an image or document and group them together. However, the visual appearance of the same is not user friendly and the group is not quickly accessible to the user. For example, in medical images, intravascular calcium objects are identified automatically upon identifying one calcium object by the physician. However the accessibility of the group is cumbersome, especially when a large number of images need to be grouped and displayed. It will be beneficial to have a method to access or display the grouped images quickly and easily.
Thus there exists a need to provide a method and system for automating the process of accessing a group of objects in an electronic document.